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April 10, 2024

DataStax Unveils New Integrations to Enhance RAG Applications with Google Cloud’s Vertex AI

SAN FRANCISCO, April 10, 2024 — DataStax has announced innovative integrations with API extensions to Google Cloud’s Vertex AI Extension and Vertex AI Search, offering developers an easier time leveraging their own data.

Enterprises have hundreds or even thousands of existing apps and data sources, and DataStax is among some of the first Google Cloud partners to collaborate on building new Vertex AI platform integrations that make it easier to connect generative AI models to existing code, data, and APIs, simplifying enterprise retrieval augmented generation (RAG).

DataStax Astra DB integrations with Vertex AI Extensions and Vertex AI Search, as well as support for Vertex AI in RAGStack, provides JavaScript, Python, C#, and any other full stack developers to leverage their data seamlessly with ease-of-use into compelling generative AI and RAG applications, getting the most out of the Google Cloud AI ecosystem.

Using these integrations, DataStax developed a generative AI application called Fashion Buddy, a fashion recommendation app that utilizes the Gemini Pro Vision foundation model in Vertex AI, Astra DB vector search, and NoSQL Assistant, a customer support chatbot that harnesses Vertex AI’s text-embedding model and Astra DB’s vector search to deliver precise answers.

The new Astra DB Vertex AI Search integration enables rapid conversational AI application development with direct access to Astra DB data, offering a no-code solution to RAG application development. This connector simplifies the orchestration of AI applications, abstracting complexity for enterprise-ready solutions, while retaining control over data and applications and ensuring privacy and security.

The new Astra DB Vertex AI Extension simplifies the integration of Vertex AI foundation models with Astra DB, facilitating CRUD operations directly within generative AI applications. Enterprises using this connector will have peace of mind now with robust enterprise controls, ensuring the highest standards of security and transparency, including IAM permissions, access transparency (AXT), data residency (DRZ), customer-managed encryption keys (CMEK), and VPC security (VPC-SC).

“Generative AI can create significant value from the data that businesses use to power their organizations,” said Ritika Suri, Director of Technology Partnerships at Google Cloud. “By utilizing Google Cloud’s technology, DataStax can help customers better connect and optimize the data needed for enterprise-grade generative AI applications.”

“At the heart of DataStax’s collaboration with Google Cloud’s Vertex AI, we are putting developers first,” said Ed Anuff, CPO, DataStax. “Offering these integrations underscores our determination to provide developers with the most advanced tools in the generative AI ecosystem.”

“DataStax’s Astra DB integration with Vertex AI simplifies GenAI app creation and provides rapid responses, global scalability, and resilience,” said Martin Brodbeck, CTO of Priceline. “We’re excited to unlock the full potential of this partnership, as we continue to enhance real-time personalized recommendations for our customers.”

For more information, read the DataStax blog on this collaboration with Google Cloud and the RAG capabilities on Astra DB here.

About DataStax

DataStax, the generative AI data company, helps developers and companies successfully create a bold new world through GenAI. We offer a one-stop generative AI Stack with everything needed for a faster, easier, path to production for relevant and responsive GenAI applications. DataStax delivers a RAG-first developer experience, with first-class integrations into leading AI ecosystem partners, so we work out with developers’ existing stacks of choice. Anyone can quickly build smart, high-growth AI applications at unlimited scale, on any cloud. Hundreds of the world’s leading enterprises, including Audi, Bud Financial, Capital One, SkyPoint Cloud, and many more, rely on DataStax to deliver GenAI.


Source: DataStax

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